About the role#
This internship focuses on scalable differentiable algorithms, specifically adjoint and automatic differentiation methods. You will connect simulations with experimental data for calibration and data assimilation using AI and machine learning. Your work will be evaluated on simulation workloads and assessed for integration into software used by researchers, engineers, and developers.
What you'll do#
- Prototype GPU-native solvers with adjoint and automatic differentiation techniques for engineering simulations.
- Integrate AI-based methods with simulation algorithms for parameter calibration, inverse problems, and data assimilation.
- Co-design numerical algorithms and differentiation strategies for GPU parallelism, memory hierarchy, mixed precision, and distributed multi-GPU execution.
- Evaluate numerical accuracy, convergence, gradient quality, and scalability on workloads in CFD, mechanics, thermal systems, and multiphysics.
- Identify promising methods and help move them toward reusable capabilities in CUDA-X libraries.
What you'll need#
- Pursuing a PhD in applied mathematics, scientific computing, computational engineering, computer science, mechanical engineering, aerospace engineering, or an equivalent program.
- Strong foundations in algorithms related to PDEs, numerical linear algebra, iterative solvers, optimization, or scientific computing.
- Research experience with adjoint methods, automatic differentiation, inverse problems, data assimilation, or gradient-aware simulation approaches.
- Experience writing numerical software in Python and C++.
- Familiarity with parallel or GPU computing.
- Ability to design computational experiments, evaluate numerical and performance tradeoffs, and communicate technical results clearly.
Location & details#
- Location: Santa Clara, California
- Term: Summer 2027
- Work Modality: On-site
- Employment Type: Full time
About NVIDIA
NVIDIA operates as a computer hardware manufacturer based in Santa Clara, California. Founded in 1993, the company focuses on accelerated computing and graphics technology. It produces hardware for markets including artificial intelligence, gaming, and data centers. The organization employs over 50,000 people and maintains a global presence.
How to get in at NVIDIA
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